/COVID19_Mortality_Predictions

This group project employs an artificial neural network and logistic regression to predict COVID19 mortality rates in individuals from the CDC Surveillance dataset. It contains a report, presentation, and several notebooks that have various functions. The primary notebooks used were Clean, Describe, Logit, MLPClassifier, and Project which is a summary notebook.

Primary LanguageJupyter NotebookMIT LicenseMIT

Grant Ferrell, Kshitij Saxena, Connor MacMillan, Nicholas Wawee

Reflection

For our project we first collected research from the CDC coronavirus case dataset for the US. We seperated the work into multiple notebooks. We created a report and presentation both of which are within this repo.